With the growth and increasing longevity of the population of older Americans, providers of health care and social services will encounter increasing numbers of persons whose functioning is impaired. Development of interventions that are effective and practical in dealing with these limitations requires thorough understanding of their determinants. Although the increasing prevalence of chronic disease with age is certain to be a major factor prior research suggest that neither disease nor age completely determines how well the elderly function. Social and psychological factors may play an important role, but how well these explain age-related differences in functional status and well-being is not well understood. Previous studies of social and psychological factors have not adequately controlled for the presence of chronic medical and psychiatric conditions, or disease severity. We propose to analyze data being collected for the Medical Outcomes Study (MOS), to explore the reasons for individual variations in health status among elderly and middle-aged adults with one or more chronic conditions. Four aspects of health status will be studied: clinical status, everyday functioning, general well-being, and mortality. We hypothesize hat health status at a point in tie and changes in health over time are affected by social circumstances and psychological factors. Multiple regression methods will be used to test this hypothesis while controlling for sociodemographic and economic characteristics, personal health practices, and medical condition (diagnosis, disease severity, and comorbidity) measured at baseline. We also proper to examine the quality of self-report data in different age groups and study factors (e.g., cognitive functioning) within these groups that might explain differences in the costs of data collection and data collection and data quality. Strengths of the proposed studies include: breadth and depth of measures of health outcomes; well-validated measures of major outcome and explanatory variables; repeated measurements over a 2- year period; and thorough baseline assessments of medical conditions. Large cross-sectional (N-22,785) and longitudinal (N- 2546) samples are available for analysis. Study participants range in age from 18-108 years; 75% of the longitudinal samples are 45 and older; 37% are 65 and older.